Combined Energy Spectra of Flux and Anisotropy Identifying Anisotropic Source Populations of Gamma-rays or Neutrinos Sheldon Campbell The Ohio State University High Energy Messengers: Connecting the Non-Thermal Extragalactic Backgrounds KICP Workshop June 9-11, 2014

Outline  Methods for identifying unresolved sources.  Flux Spectrum  Angular Power Spectrum  Combining Flux and Angular techniques for a spectral line search.  Some new discoveries presented here first. Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

How to Identify Unresolved Sources of Radiation?  Spectral Analyses of Diffuse Radiation 1. Flux Spectrum  New features over the energy range of the unresolved sources.  Constrains the source emission and mean number distribution. 2. Angular Power Spectrum  Additionally constrains the angular distribution of the sources. Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Example: “Discovering” Dark Matter  Requires establishing a framework that accounts for:  the astrophysical dark matter content.  the dark matter particle properties.  the dark matter clustering properties.  Dark matter “hint” features make good case studies.  These methods are applicable to any anisotropy measurements and analyses of the detection of “events” from anisotropic sources. Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Flux Methodology: Spectral Line The lack of a 135 GeV line in the diffuse gamma-ray background for high substructure content further strains the plausibility of a dark matter interpretation. Ng, Laha, SC, et al. (2014) Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Complementary Approach : Anisotropies Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Sensitive to the density profile of the Galactic halo and subhalos (simulations). Sensitive to the subhalo abundance and mass range (simulations). Calore et al. (2014) Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Anisotropy of a Spectral Line SC, CETUP Proceedings (2014) Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Unbiased Estimator of Angular Power Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Usual Statistical Error Estimate Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Event-Limited Experiments are Shot-Dominated Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Growth of Signal Strength E.g., A 135 GeV Line Signal Strength = Signal / Measurement Uncertainty SC, Beacom (2013) Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Complementary Flux/Anisotropy 130 GeV Line Search in the Diffuse Bkg. The Fluctuation Angular Power Spectrum (Clustering) vs. Substructure Intensity Boost SC, Beacom (2013) This is the first joint flux/anisotropy analysis to constrain both the intensity and angular distribution of a spectral feature. New research results modify this anisotropy sensitivity. Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Improving Our Understanding of the Statistical Variance  Some conceptual difficulties with using the cosmic variance as we did.  Cosmic variance is a theoretical error, which applies when making physical inferences about our models based on data.  The angular power spectrum measurement should be able to be made independently of any model.  We should not need to assume the signal is Gaussian- distributed.  Investigations have lead to a new formula for the model- independent statistical variance of the angular power spectrum of events from a background distribution. Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Compare to Gaussian Cosmic Variance Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

Conclusions  Distinguishable components of astrophysical radiation may be separated through different emission features, or different spatial morphologies.  Combining both search techniques increases sensitivity to weak signals.  An corrected statistical variance of the angular power spectrum of events is presented. This is applicable to experiments of high energy gamma-rays, cosmic rays, neutrinos, and cosmological galaxy surveys. Sheldon Campbell, Combined Energy Spectra of Flux and Anisotropy KICP Workshop on High Energy Messengers 6/10/2014

What is a Good Way to Turn an Indirect Detection Hint to Dark Matter Discovery?  We’ve seen a hint. Now that we know where to look, go for the diffuse signal!  It verifies the particle properties observed with the hint.  It establishes the clustering properties of dark matter— heretofore unobserved. For local annihilations:

Need Consistent DM Distribution for Observed Scenario Ng, Laha, SC, et al. (2014)

Case Study 1: GeV Galactic Center Excess Daylan et al. (2014) Abazajian et al. (2014)

Case Study 1: GeV Galactic Center Excess  We have a signal consistent with:  thermal relic annihilation,  annihilation to heavy quarks and/or leptons,  a GeV WIMP.  First detection of WIMP at a cuspy galactic center is the textbook expectation.  In this scenario, the distributions of Milky Way and M31 satellites are unusual. Prediction for diffuse background?

Flux Methodology: GeV GC Excess Ng, Laha, SC, et al. (2014)

Flux Methodology: GeV GC Excess Ng, Laha, SC, et al. (2014)

 Gamma-ray excess from Galactic center.  ~4 standard deviations above background.  Source morphology consistent with spherical cusp. Fermi-LAT Collaboration (2013)  Some features of the signal made the dark matter explanation less compelling:  spectral line feature was narrower than the energy resolution.  a similar, though smaller, line in the Earth limb.

Predictions:  If due to a systematic effect  the apparent signal will persist in all regions until the source is determined.  If the signal is dark matter annihilation  the line will broaden and its significance will grow.  the line may be observed in other dark matter regions.  If the signal is a statistical fluctuation  the signal will shrink and disappear.

 The fulfillment of the 3 rd prediction gives support to the hypothesis that the line was a statistical fluctuation. Weniger (2012)

Anisotropy with Continuous Annihilation Spectra Siegal-Gaskins, Pavlidou, PRL 102 (2009)

Fluct. Angular Power Spectra from DM Fornasa et al., arXiv:

Weighted Average Power Spectrum